This invention relates to X-ray diffraction systems. X-ray diffraction is a non-destructive technique for the qualitative and quantitative analysis of crystalline material samples, which are generally provided in the form of single crystals. In accordance with this technique, an X-ray beam is generated by an X-ray tube with a stationary anode, by a conventional rotating anode X-ray source or by a synchrotron source and directed toward the material sample under investigation. When the X-rays strike the sample, they are diffracted according to the atomic structure of the sample.
A typical laboratory system 100 for performing single crystal diffraction experiments normally consists of five components as shown in FIG. 1. The components include an X-ray source 102 that produces a primary X-ray beam 104 with the required radiation energy, focal spot size and intensity. X-ray optics 106 are provided to condition the primary X-ray beam 104 to a conditioned, or incident, beam 108 with the required wavelength, beam focus size, beam profile and divergence. A goniometer 110 is used to establish and manipulate geometric relationships between the incident X-ray beam 108, the crystal sample 112 and the X-ray sensor 114. The incident X-ray beam 108 strikes the crystal sample 112 and produces scattered X-rays 116 which are recorded in the sensor 114. A sample alignment and monitor assembly comprises a sample illuminator 118, typically a laser, that illuminates the sample 112 and a sample monitor 120, typically a video camera, which generates a video image of the sample to assist users in positioning the sample in the instrument center and monitoring the sample state and position.
The goniometer 110 allows the crystal sample 112 to be rotated around several axes. Precise crystallography requires that the sample crystal 112 be aligned to the center of the goniometer 110 and maintained in that center when rotated around the goniometer rotational axes during data collection. During exposure, the sample (a single crystal of the compound of interest) is rotated in the X-ray beam 108 through a precise angular range with a precise angular velocity. The purpose of this rotation is to predictably bring Bragg angle reflections from each atomic plane of the sample into resonance with the incident beam 108 for the same period of time. During this time, called the charge integration time, the pixels of the sensor receive and integrate the X-ray signals.
Current generation X-ray area sensors 114 used for crystallography, include charge coupled devices (CCDs), Image Plates and CMOS sensors. CMOS Active Pixel Sensors (APS) have a number of advantages compared to CCD detectors for applications in X-ray detection. The advantages include high speed readout, high quantum gain and large active areas. However, the readout noise (comprised primarily of thermal noise on capacitors, commonly called kTC noise, 1/f noise and dark current shot noise) of these devices is typically about an order of magnitude larger than the readout noise of CCDs.
One conventional method for reducing the effective readout noise in CMOS sensors is to oversample the charge stored in the pixel sites. More specifically, many CMOS APS devices can be read out non-destructively which means the charge in a given pixel may be sampled multiple times without resetting the value of the charge. An article entitled “Demonstration of an Algorithm for Read-Noise Reduction in Infrared Arrays”, A. M. Fowler and Ian Gatley, The Astrophysical Journal, 353:L33-L34, (1990) describes a technique in which an array is readout non-destructively N times after charge integration as shown schematically in FIG. 1 in order to reduce noise.
FIG. 2 is a schematic diagram 200 showing the charge in a pixel i on the vertical axis versus time on the horizontal axis. At the frame start time 202, the charge in the pixel is zero. The charge then linearly increases during the frame exposure time until the end of the frame at time 204 at which time a shutter is closed in order to prevent further X-rays from charging the pixel. Then, in this example, three non-destructive reads, 206, 208 and 210 are performed. Finally, a destructive read 212 is performed in order to reset the charge in the pixel to zero in preparation for the next exposure.
Theoretically, by observing the same random variable N times, the noise can be reduced by a factor of
      1          N        .In the aforementioned article, Fowler et al showed experimentally that the effective noise is reduced by a factor very close to this theoretically expected factor. The same technique is also described for a specialized CCD with a non-destructive readout capability in U.S. Pat. No. 5,250,824. However, reducing noise in this manner has the obvious disadvantage that the readout dead time is increased by a factor of N times the array readout time. For example, if the array is oversampled nine times then the readout noise is reduced by approximately √{square root over (9)}=3 times but the total readout dead time is increased by nine times. In both prior art cases mentioned above, this technique was proposed primarily for astronomical observations where the increase in readout dead time was acceptable. However, for more dynamic applications this increase in readout dead time is most often unacceptable.
A different approach is described in an article entitled “Far-infrared focal plane development for SIRT”, E. T. Young, M. Scutero, G. Rieke, T. Milner, F. J. Low, P. Hubbard, J. Davis, E. E. Haller, and J. Beeman, Infrared Readout Electronics, Proceedings SPIE, v. 1684, pp. 63-74. (April 1992). In accordance with this technique called “Multiple Sample Correlation”, a CMOS pixel is sampled N times during charge integration (that is, while the sensor is being exposed to the X-rays). This sampling is shown schematically in FIG. 3, which is a schematic diagram 300 also showing the charge in a pixel i on the vertical axis versus time on the horizontal axis. At the frame start time 302, the charge in the pixel is zero. The charge then linearly increases during the frame exposure time until the end of the frame at time 304 at which time a shutter is closed in order to prevent further X-rays from charging the pixel. However, unlike the previous technique, in this example eight non-destructive reads 306 are made during the pixel integration time. A final destructive read 308 is made at the end of the frame time 304 to reset the pixel charge to zero in preparation for the next frame.
A similar technique was also described in an article entitled “A low-noise oversampling signal detection technique for CMOS image sensors”, N. Kawai, S. Kawahito, and Y. Tadokoro, Proceedings of IEEE Instrumentation and Measurement Technology Conference, Anchorage, Ak., v. 1, pp. 256-268 (May 2002). In accordance with this latter technique, the output of a CMOS imager is sampled N times. The resultant signals are then fed back into the readout circuit through a D-to-A converter. This technique allows the same sort of
  1      N  noise reduction as the previous technique without having to read the array out N times (thus reducing the external data rate).
While the general approach of using multiple non-destructive readouts to improve the noise or dynamic range performance of a sensor is well established, the prior art assumes that the illumination source is invariant with time or varies in a predictable fashion. In particular, the aforementioned prior art techniques that sample during integration implicitly assume that the scene being imaged is static. That is, the photon flux incident on each pixel is constant during the pixel integration time. Of course, this is not the case in an X-ray diffraction system in which the diffracted X-rays serve as the illumination source.
Also, the aforementioned prior art techniques that sample during integration assume that the sensor response is otherwise ideal. In particular, they assume that the sensor response is perfectly linear. However, in an actual CMOS sensor, the output is not linear but typically shows nonlinearities of a few percent. Therefore, a simple application of the prior art techniques will not reduce the noise in a CMOS sensor output due to the errors induced by the sensor nonlinearity. The prior art also neglects the contributions of dark current noise and fixed pattern noise.
It would be strongly desirable to reduce the noise of CMOS devices while preserving the other benefits.